利用化学钟和贝叶斯推断进行恒星定年
Stellar dating using chemical clocks and Bayesian inference
摘要：
测定恒星的年龄是一项重大挑战，对许多天体物理学领域都有着深远的影响。最有前途的技术之一是使用化学丰度。最近的空间和地面设施通过精确的观测改善了恒星的数量。这为使用贝叶斯推断工具最大化我们可以从中提取的信息打开了大门。我们的目标是提出准确和可靠的恒星年龄估计FGK恒星的化学丰度和恒星参数。我们使用了最灵活的贝叶斯推断技术之一（分层贝叶斯模型），以超越目前使用化学丰度进行恒星定年的可能性。我们的模型是数据驱动的模型。我们使用的训练集，已在文献中提出的年龄估计等时线和准确的恒星丰度和一般特征。该模型的核心是将某些丰度比作为恒星性质（包括年龄）的线性组合。我们收集了四个不同的测试集，以评估我们模型的准确性，精确度和限制。我们还训练了一个仅使用化学丰度的模型。我们发现，我们的年龄估计值与来自星震学、其他精确来源以及10颗盖亚基准恒星的年龄估计值吻合得很好。我们的估计值与参考值的平均绝对差为0.9Ga，平均差为0.01Ga。当使用疏散星团时，我们对毕宿星、NGC 2632、Ruprecht 147和IC 4651的观测结果非常一致。我们还发现了异常值，这些异常值反映了训练集有效范围的极限处的化学特性和/或星。仅使用化学丰度的模型显示出稍差的平均绝对差（1.18 Ga）和平均差（-0.12 Ga）。
英文摘要：
Dating stars is a major challenge with a deep impact on many astrophysical fields. One of the most promising techniques for this is using chemical abundances. Recent space- and ground-based facilities have improved the quantity of stars with accurate observations. This has opened the door for using Bayesian inference tools to maximise the information we can extract from them. Our aim is to present accurate and reliable stellar age estimates of FGK stars using chemical abundances and stellar parameters. We used one of the most flexible Bayesian inference techniques (hierarchical Bayesian models) to exceed current possibilities in the use of chemical abundances for stellar dating. Our model is a data-driven model. We used a training set that has been presented in the literature with ages estimated with isochrones and accurate stellar abundances and general characteristics. The core of the model is a prescription of certain abundance ratios as linear combinations of stellar properties including age. We gathered four different testing sets to assess the accuracy, precision, and limits of our model. We also trained a model using chemical abundances alone. We found that our age estimates and those coming from asteroseismology, other accurate sources, and also with ten Gaia benchmark stars agree well. The mean absolute difference of our estimates compared with those used as reference is 0.9 Ga, with a mean difference of 0.01 Ga. When using open clusters, we reached a very good agreement for Hyades, NGC 2632, Ruprecht 147, and IC4651. We also found outliers that are a reflection of chemical peculiarities and/or stars at the limit of the validity ranges of the training set. The model that only uses chemical abundances shows slightly worse mean absolute difference (1.18 Ga) and mean difference (-0.12 Ga).
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